Contaminant source identification of water distribution networks using cultural algorithm

In recent years, the drinking water pollution incident occurred frequently, a serious threat to social stability and security. By using the sensor networks real-time monitoring the urban water supply networks, the water pollution event probability can be greatly reduced. But knowing how to use the water quality monitor sensor networks to collect information to identify pollution sources is still a challenging problem. In this paper, we formulate the contaminant source identification problem into an optimization problem, and then design the cultural algorithm to solve it by considering different sizes of water supply networks as the experimental data. Finally, the experimental results verify the effectiveness and robustness of the proposed method.